Volodymyr Babich

Competition and Diversification Effects in Supply Chains with Supplier Default Risk

We study the effects of disruption risk in a supply chain where one retailer deals with competing risky suppliers who may default during their production lead times. The suppliers, who compete for business with the retailer by setting wholesale prices, are leaders in a Stackelberg game with the retailer. The retailer, facing uncertain future demand, chooses order quantities while weighing the benefits of procuring from the cheapest supplier against the advantages of order diversification. For the model with two suppliers, we show that low supplier default correlations dampen competition among the suppliers, increasing the equilibrium wholesale prices. Therefore the retailer prefers suppliers with highly correlated default events, despite the loss of diversification benefits. In contrast, the suppliers and the channel prefer defaults that are negatively correlated. However, as the number of suppliers increases, our model predicts that the retailer may be able to take advantage of both competition and diversification.

Supply Disruptions, Asymmetric Information, and a Backup Production Option

We study a manufacturer that faces a supplier privileged with private information about supply disruptions. We investigate how risk-management strategies of the manufacturer change and examine whether risk-management tools are more or less valuable in the presence of such asymmetric information. We model a supply chain with one manufacturer and one supplier, in which the suppliers reliability is either high or low and is the suppliers private information. On disruption, the supplier chooses to either pay a penalty to the manufacturer for the shortfall or use backup production to fill the manufacturers order. Using mechanism design theory, we derive the optimal contract menu offered by the manufacturer. We find that information asymmetry may cause the less reliable supplier type to stop using backup production while the more reliable supplier type continues to use it. Additionally, the manufacturer may stop ordering from the less reliable supplier type altogether. The value of supplier backup production for the manufacturer is not necessarily larger under symmetric information; for the more reliable supplier type, it could be negative. The manufacturer is willing to pay the most for information when supplier backup production is moderately expensive. The value of information may increase as supplier types become uniformly more reliable. Thus, higher reliability need not be a substitute for better information.

Contracting with Asymmetric Demand Information in Supply Chains

When a retailer holds no private information, a powerful supplier can use several contract types to extract for herself the first-best channel profit, leaving the retailer nothing but his reservation profit. In the case where the retailer holds private information on the probability distribution of market demand, most well analyzed contracts do not allow the supplier to achieve for herself the first-best channel profit. In equilibrium, the retailer is able to extract an information rent above his reservation profit, and the overall channel may deviate from its first-best solution. This paper shows that using judicially designed wholesale price contracts involving a buyback policy, a supplier can theoretically avoid paying any information rent to the privately informed retailer, and, at the same time, can extract all the first-best channel profit.

Risk, Financing and the Optimal Number of Suppliers

Should firms in developed economies work with more or fewer suppliers than firms in developing economies? More generally, how does the number of suppliers for a firm depend on the firm’s economic environment? To answer these questions we identify several economic and business factors that might affect the number of suppliers (and that separate developed and developing economies): supply risk, fixed costs of working with suppliers, and access to financing (particularly trade-credit financing).

Decentralized Supply Risk Management

In a 2008 survey of 138 companies, 58% reported that they suffered financial losses within the last year due to a supply disruption. This article emphasizes the challenges and opportunities in supply risk management arising from the decentralized nature of supply chains and highlight how supply risks influence the interactions among firms in supply networks, review insights into decentralized supply risk management from the extant academic research and point out important future research directions.

Does a Procurement Service Provider Generate Value for the Buyer Through Information About Supply Risks

We consider a supply chain with one buyer and two suppliers who are subject to disruptions and whose likelihoods of disruption are their private information. In such a setting, does the buyer benefit from engaging the services of a better-informed procurement service provider (PSP) compared to procuring directly from the suppliers? Intuition might suggest that hiring a PSP is always the right choice because the PSP’s knowledge of the supply base improves supplier selection and management. On the other hand, earlier studies prove that using a PSP purely for its superior knowledge about supply costs is always worse for a buyer than contracting with the suppliers directly. Our answer to this research question is more nuanced. Contrary to the findings of earlier studies, we find that the buyer may benefit from using a PSP. We identify, quantify, and explain all of the benefits and the costs of using a PSP, and describe conditions under which the benefits exceed the costs. The benefits of using a PSP are deriv...

Manufacturers' Competition and Subsidies to Suppliers

Dealing with risky suppliers is a part of everyday business for manufacturers. For example, the domestic automotive supply industry has faced numerous hardships as some of its largest firms have flirted with bankruptcy, or have been subsumed by Chap 11 over the past few years. Nearly 30% of the pre-existing North American automotive supply base had filed for bankruptcy by the end of 2008. Half are predicted to file for bankruptcy before the end of 2010.

Optimality of Myopic Policies for Dynamic Lot-Sizing Problems in Serial Production Lines with Random Yields and Autoregressive Demand

We study lot-size policies in a serial, multistage manufacturing/inventory system with two key generalizations, namely 1 random yields at each production stage and 2 an autoregressive demand process. Previous research shows that the optimal policies in models with random yields even in models with a single installation lack the familiar order-up-to structure and are not myopic. Thus, dynamic programming algorithms are needed to compute optimal policies, and one encounters the “curse of dimensionality”; this is exacerbated here by the need to expand the size and dimension of the state space to accommodate the autoregressive demand feature. Nevertheless, although our model is more complex, we prove that there is an optimal policy with the order-up-to feature and, more importantly, that the optimal policy is myopic. This avoids the computational burden of dynamic programming. Our results depend on two assumptions concerning the stochastic yield, namely that the expected yield at a work station is proportional to the lot size, and the distribution of the deviation of the yield from its mean does not depend on the lot size. We introduce the concept of echelon-like variables, a generalization of Clark and Scarfs classical concept of echelon variables, to derive the structure of optimal policies. Furthermore, we show that the same kind of policy is optimal for several criteria: infinite-horizon discounted cost, infinite-horizon long-run average cost, and finite-horizon discounted cost with the appropriate choice of the salvage value function.

Unit-Contingent Power Purchase Agreement and Asymmetric Information About Plant Outage

This paper analyzes a unit-contingent power purchase agreement between an electricity distributor and a power plant. Under such a contract the distributor pays the plant a fixed price if the plant is operational and nothing if plant outage occurs. Pricing a unit-contingent contract is complicated by the fact that the plants true status is its private information. The difference between the electricity spot price and the unit-contingent contract price provides an incentive for the plant to misreport its status and earn profit at the distributors expense. To prevent misreporting, the distributor may inspect the plant and levy penalties if misreporting is discovered. We find that some type of misreporting under certain circumstances can benefit both the plant and the distributor, because it serves as a risk-allocation mechanism between the two parties. We show that such a risk-allocation mechanism is equivalent to using state-contingent options and prohibiting misreporting.

Computationally Simple and Unified Approach to Finite and Infinite Horizon Clark-Scarf Inventory Model

In this article, it is shown that an easily computed and simply structured policy for making work-order decisions is optimal in the Clark–Scarf inventory model. That is a model of a make-to-stock multistage serial manufacturing process with convex costs of finished goods inventory, a setup cost for purchasing, linear costs of work-in-process inventories, and backlogging of excess demand. The criteria used in this article include the expected present value of costs (in the finite and infinite horizons) and the long-run average cost per period. Moreover, the same myopic policy that is optimal for the finite-horizon model is optimal also for the infinite-horizon model. This permits a unified approach to the various criteria.